SOTAVerified

Language Modelling

A language model is a model of natural language. Language models are useful for a variety of tasks, including speech recognition, machine translation, natural language generation (generating more human-like text), optical character recognition, route optimization, handwriting recognition, grammar induction, and information retrieval.

Large language models (LLMs), currently their most advanced form, are predominantly based on transformers trained on larger datasets (frequently using words scraped from the public internet). They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.

Source: Wikipedia

Papers

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Showing 5651–5700 of 17610 papers

TitleStatusHype
A Hybrid Attention Framework for Fake News Detection with Large Language Models—0
ALoFTRAG: Automatic Local Fine Tuning for Retrieval Augmented GenerationCode0
The Value of Nothing: Multimodal Extraction of Human Values Expressed by TikTok Influencers—0
SeRpEnt: Selective Resampling for Expressive State Space Models—0
QualityFlow: An Agentic Workflow for Program Synthesis Controlled by LLM Quality Checks—0
Trojan Detection Through Pattern Recognition for Large Language Models—0
Know "No'' Better: A Data-Driven Approach for Enhancing Negation Awareness in CLIP—0
AI Based Font Pair Suggestion Modelling For Graphic Design—0
DNA 1.0 Technical Report—0
Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation—0
A Vision-Language Framework for Multispectral Scene Representation Using Language-Grounded Features—0
Hierarchical Autoregressive Transformers: Combining Byte- and Word-Level Processing for Robust, Adaptable Language Models—0
BoK: Introducing Bag-of-Keywords Loss for Interpretable Dialogue Response GenerationCode0
CLIP-PCQA: Exploring Subjective-Aligned Vision-Language Modeling for Point Cloud Quality AssessmentCode0
Evolving Deeper LLM Thinking—0
Adapting Large Language Models for Character-based Augmentative and Alternative Communication—0
FLORA: Formal Language Model Enables Robust Training-free Zero-shot Object Referring Analysis—0
Sympathy over Polarization: A Computational Discourse Analysis of Social Media Posts about the July 2024 Trump Assassination Attempt—0
Multi-stage Training of Bilingual Islamic LLM for Neural Passage Retrieval—0
Steering Large Language Models with Feature Guided Activation Additions—0
Large Language Model is Secretly a Protein Sequence Optimizer—0
mGeNTE: A Multilingual Resource for Gender-Neutral Language and Translation—0
Lost in Translation, Found in Context: Sign Language Translation with Contextual Cues—0
Making Your Dreams A Reality: Decoding the Dreams into a Coherent Video Story from fMRI Signals—0
An LLM-Guided Tutoring System for Social Skills Training—0
Augmenting a Large Language Model with a Combination of Text and Visual Data for Conversational Visualization of Global Geospatial Data—0
Double Visual Defense: Adversarial Pre-training and Instruction Tuning for Improving Vision-Language Model Robustness—0
Augmenting Human-Annotated Training Data with Large Language Model Generation and Distillation in Open-Response Assessment—0
CityLoc: 6DoF Pose Distributional Localization for Text Descriptions in Large-Scale Scenes with Gaussian Representation—0
Applying General Turn-taking Models to Conversational Human-Robot Interaction—0
Induced Model Matching: Restricted Models Help Train Full-Featured ModelsCode0
Leveraging LLM Agents for Translating Network Configurations—0
LoRS: Efficient Low-Rank Adaptation for Sparse Large Language Model—0
MAGNET: Augmenting Generative Decoders with Representation Learning and Infilling Capabilities—0
Omni-RGPT: Unifying Image and Video Region-level Understanding via Token Marks—0
Real-time Verification and Refinement of Language Model Text Generation—0
Large Language Models For Text Classification: Case Study And Comprehensive Review—0
Large Language Model Interface for Home Energy Management Systems—0
Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT—0
Hierarchical Autoscaling for Large Language Model Serving with Chiron—0
ADAM-1: AI and Bioinformatics for Alzheimer's Detection and Microbiome-Clinical Data Integrations—0
A Driver Advisory System Based on Large Language Model for High-speed Train—0
Enhancing Image Generation Fidelity via Progressive PromptsCode0
Audio-CoT: Exploring Chain-of-Thought Reasoning in Large Audio Language Model—0
A Proposed Large Language Model-Based Smart Search for Archive System—0
Pre-Trained Large Language Model Based Remaining Useful Life Transfer Prediction of Bearing—0
TiEBe: Tracking Language Model Recall of Notable Worldwide Events Through TimeCode0
LLMic: Romanian Foundation Language Model—0
Multi-megabase scale genome interpretation with genetic language models—0
LLM360 K2: Building a 65B 360-Open-Source Large Language Model from Scratch—0
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All datasetsWikiText-103Penn Treebank (Word Level)enwik8The PileWikiText-2LAMBADAOne Billion WordText8Penn Treebank (Character Level)Hutter PrizeOpenWebTextSALMon

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67—Unverified
2GRUValidation perplexity53.78—Unverified
3LSTMValidation perplexity52.73—Unverified
4LSTMTest perplexity48.7—Unverified
5Temporal CNNTest perplexity45.2—Unverified
6TCNTest perplexity45.19—Unverified
7GCNN-8Test perplexity44.9—Unverified
8Neural cache model (size = 100)Test perplexity44.8—Unverified
9Neural cache model (size = 2,000)Test perplexity40.8—Unverified
10GPT-2 SmallTest perplexity37.5—Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47—Unverified
2Seq-U-NetTest perplexity107.95—Unverified
3GRU (Bai et al., 2018)Test perplexity92.48—Unverified
4R-TransformerTest perplexity84.38—Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7—Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7—Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93—Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4—Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2—Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67—Unverified
2HypernetworksBit per Character (BPC)1.34—Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33—Unverified
4LN HM-LSTMBit per Character (BPC)1.32—Unverified
5ByteNetBit per Character (BPC)1.31—Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27—Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25—Unverified
8Large mLSTMBit per Character (BPC)1.24—Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23—Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22—Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33—Unverified
2OPT 125MTest perplexity32.26—Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1—Unverified
4OPT 1.3BTest perplexity19.55—Unverified
5GPT-Neo 125MTest perplexity17.83—Unverified
6OPT 2.7BTest perplexity17.81—Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12—Unverified
8GPT-Neo 1.3BTest perplexity11.46—Unverified
9Transformer 125MTest perplexity10.7—Unverified
10GPT-Neo 2.7BTest perplexity10.44—Unverified